/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         http://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/

#include "itkGaussianSpatialFunction.h"
#include "itkMath.h"
#include "itkTestingMacros.h"

int
itkGaussianSpatialFunctionTest(int argc, char * argv[])
{
  if (argc < 3)
  {
    std::cout << "Usage: " << itkNameOfTestExecutableMacro(argv) << " scale normalized" << std::endl;
    return EXIT_FAILURE;
  }

  constexpr unsigned int Dimension = 3;
  using PixeltType = double;

  using GaussianSpatialFunctionType = itk::GaussianSpatialFunction<PixeltType, Dimension>;

  using ArrayType = GaussianSpatialFunctionType::ArrayType;
  using InputType = GaussianSpatialFunctionType::InputType;

  // Create and initialize the Spatial function

  GaussianSpatialFunctionType::Pointer gaussianSpatialFunction = GaussianSpatialFunctionType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(gaussianSpatialFunction, GaussianSpatialFunction, SpatialFunction);

  ArrayType mean;
  mean[0] = 13;
  mean[1] = 17;
  mean[2] = 19;
  gaussianSpatialFunction->SetMean(mean);
  ITK_TEST_SET_GET_VALUE(mean, gaussianSpatialFunction->GetMean());

  ArrayType sigma;
  sigma[0] = 5;
  sigma[1] = 7;
  sigma[2] = 9;
  gaussianSpatialFunction->SetSigma(sigma);
  ITK_TEST_SET_GET_VALUE(sigma, gaussianSpatialFunction->GetSigma());

  double scale = std::stod(argv[1]);
  gaussianSpatialFunction->SetScale(scale);
  ITK_TEST_SET_GET_VALUE(scale, gaussianSpatialFunction->GetScale());

  auto normalized = static_cast<bool>(std::stoi(argv[2]));
  gaussianSpatialFunction->SetNormalized(normalized);
  ITK_TEST_SET_GET_VALUE(normalized, gaussianSpatialFunction->GetNormalized());

  if (normalized)
  {
    gaussianSpatialFunction->NormalizedOn();
    ITK_TEST_SET_GET_VALUE(true, gaussianSpatialFunction->GetNormalized());
  }
  else
  {
    gaussianSpatialFunction->NormalizedOff();
    ITK_TEST_SET_GET_VALUE(false, gaussianSpatialFunction->GetNormalized());
  }


  // Test the evaluation of the Gaussian spatial function
  //

  // Evaluate it at the center of the Gaussian
  InputType point;
  point[0] = mean[0];
  point[1] = mean[1];
  point[2] = mean[2];

  double computedValueAtMean = gaussianSpatialFunction->Evaluate(point);

  double expectedValueAtMean = 1.0;
  if (gaussianSpatialFunction->GetNormalized())
  {
    const double oneDimensionalFactor = std::sqrt(2.0 * itk::Math::pi);
    const double factor = oneDimensionalFactor * oneDimensionalFactor * oneDimensionalFactor;
    expectedValueAtMean = scale / (sigma[0] * sigma[1] * sigma[2] * factor);
  }
  else
  {
    constexpr double oneDimensionalFactor = 1.0;
    const double     factor = oneDimensionalFactor * oneDimensionalFactor * oneDimensionalFactor;
    expectedValueAtMean = scale / factor;
  }

  if (itk::Math::NotAlmostEquals(expectedValueAtMean, computedValueAtMean))
  {
    std::cout << "Error in point " << point << ": ";
    std::cout << "expected: " << expectedValueAtMean << ", but got " << computedValueAtMean << std::endl;
    std::cout << "Test failed" << std::endl;
    return EXIT_FAILURE;
  }

  return EXIT_SUCCESS;
}
